code: def _src_embed_with_learned_positional(c: TransformerConfigs):
      """
      Source embedding with learned positional encodings
      """
      return EmbeddingsWithLearnedPositionalEncoding(
          c.d_model, c.n_src_vocab
      )
  
imports: import copy
  import torch.nn
  from labml.configs import BaseConfigs, option, calculate, aggregate
  from labml_helpers.module import Module
  from .feed_forward import FeedForward
  from .mha import MultiHeadAttention
  from .models import EmbeddingsWithPositionalEncoding, EmbeddingsWithLearnedPositionalEncoding, TransformerLayer, Encoder, Decoder, Generator, EncoderDecoder
label_desc: Use image node_id 14 for calling a global function with example usage: _src_embed_with_learned_positional(c) and returns: EmbeddingsWithLearnedPositionalEncoding